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									  Monitoring health system performance -
synthesis of some experiences from low-income

     Dina Balabanova, Tim Powell-Jackson, Richard Coker, Kara Hanson &
                                                             Anne Mills

              London School of Hygiene and Tropical Medicine

                Health System Metrics, Glion sur Montreux,
                         28-29 September 2006

   Background
   Complexity
   Objectives and methods
   Measurement
   Health financing
   Health care delivery
   Emerging issues
   Conclusions
   Commitment to invest in health systems is unprecedented, but will
    not last unless it is possible to show results
   Currently poor health information available but demand for
    improved health system metrics (national / international)

   Opportunities
    – Health System Metrics and other initiative seeking to strengthen HIS
    – Commitment to the health MDGs – need to measure progress
    – Growing consensus of importance of measurement strategies & monitoring &
      evaluation built into programme planning cycles

   Threats
    – Limited resources for health information and sustainability
    – Capacity constraints (in the health and social sectors)
                   Objectives & Methods
   Purpose of the study: a review of some low-income countries’
    experiences with health system performance monitoring and use of
   Case study countries:
     –   Georgia
     –   Rwanda
     –   Uganda
     –   West Bengal, India
     –   Material from other countries
   Selection criteria
   Analytical approaches:
     – uses the WHO health system performance framework
     – synthesis around common themes and issues
     – identifying unique lessons in each type of context
   How should health system performance be measured?
     – Increasingly multiple contacts with the system, chronic diseases
     – Outcomes determined by different care components, sectors
     – Need for system-wide and inter-sectoral indicators

   Tension between international (donor-driven) demands and
    country-level agendas and needs

   Use of normative approaches imply causality

   To what extent monitoring influences policy?

   Impact of measurement on health systems, e.g. Indicators that are
    measured often improve

   Monitoring information may be complex to interpret where a
    range of interventions co-exist.

What approaches are taken to measure health
 system performance in the study countries?
  What is measured ?
Data                      Georgia                  Rwanda                       Uganda                 West Bengal
Demographic               Census (2002)            Census (2002)                Census (2002)              Census (2001)

                                                                               NHA (2001), public
                                                                              expenditure reviews,
Health financing           NHA (2004)                NHA (2003)              Tracking Study (2001)           NHA (2001)

Health outcomes incl.   RHS (2005) & MICS
                            (2006), Vital        DHS (2005), HMIS
births and deaths       registration & HMIS          (facility)                   DHS (2004)                 DHS (2005)

Co-coverage of
                        MICS (2006) & RHS
interventions                 (2005)                 DHS (2005)                   DHS (2004)                 DHS (2005)

Human resources               HMIS                  HR inventory                 HR inventory                   HMIS
                                                HMIS, SAM (2004) &
                                                 Service Provision
                        HMIS & SAM (2005-       Assessment Survey           HMIS, SAM (2004), Area
Service provision              06)                    (2001)                  Team assessments                  HMIS

Quality                         n/a                      n/a                 Various / accreditation             n/a
                        Immunisation, TB,      Immunisation, malaria,       Immunisation, malaria,        Malaria, RCH, TB,
Vertical programme         HIV/AIDS              HIV/AIDS, TB etc.            HIV/AIDS, TB etc.        Leprosy, Polio, HIV/AIDS
monitoring                                                                                                       etc.

                                              Sentinel sites (HIV), early
Disease surveillance          IDRS
                                               warning system, IDRS           Sentinel sites (HIV)              HMIS
     Health financing

How has information been used?
    Where are the gaps?
  What challenges remain?
      Use of health financing information
   Identification of financing gaps and advocacy for increased allocation
    of funds to health (Rwanda)

   Health sector leadership and management of funds (Tanzania,

   Equity of health financing in the health system (South Africa, Rwanda)

   Protection against the financial burden of ill health (Mexico)

   Resource allocation with the health sector (Rwanda)
     Gaps in health financing information
   Private health expenditures – difficult to collect compared to
    public and external health financing sources

   Coverage of NHA relatively low in developing countries but

   Health financing data at decentralised levels for local decision-

   Financial burden of ill health and impact on impoverishment at
    the household level
     National Health Accounts in Africa
                      Number of NHA Rounds 1994 – 2004

NHA Rounds




                  0      5     10         15           20   25   30
                                    Countries (N=46)
                     Remaining challenges
   Institutionalisation of NHA into the routine activities of Government

   Underlying problems in Public Expenditure Management systems and data

   Timeliness of data (NHAs and household surveys)

   Collection of private expenditure health financing data

   Tension between disease expenditure and general health expenditure
    financial tracking

   Addressing the needs of in-country policy makers vis-à-vis that of external
   Health care delivery

How has information been used?
    Where are the gaps?
  What challenges remain?
    Use of information: country examples
West Bengal, India
Aim: to monitor the performance of public sector programmes. Improve
    accountability and planning at national level
   Standard service use indicators & regular meetings in PHC facilities

Aim: to link health system performance monitoring to SWAPs and national
   policy process. Allows policy adjustment.
   Data used in the annual health sector review process and to inform the
    development of annual plans
   District league tables to rank performance of districts & motivate
    districts to improve indicators.
   Tracking surveys – at the start of SWAP, 2001- to assess Govt systems
    (financial procedures, drug distribution, HR deployment)
          Major gaps in measurement
   Private sector – service use, service availability
    (infrastructure, human resources, services
   Vital events
   Efficiency of health system
   Quality of health care
   Effective coverage
                    Remaining challenges

   Low capacity and motivation to use data:
     – Locally
     – For decision-making or for policy initiatives
   Lack of ownership by health providers, who are not involved in
    designing of monitoring procedure and indicators
   Capacity for analysis concentrated at central level
   Feedback to lower levels is limited, poor internal feedback
   HMIS is often mistrusted
   Selection of indicators often creates distortions
   Information systems do not reflect move from project to system
     – India: ‘critical milestones’ & vertical project indicators
Emerging issues
            Data quality and reliability

   Existing information systems, but data inaccessible or
    inappropriate to needs and policy process
   Developing parallel monitoring frameworks rather than
    adapting & use of existing data: concerns for complexity and
    data reliability

   HIS not always reflecting reform developments
   Limited external data audit and reliance on single data
    sources (Rwanda, Uganda)
   Technology involved in data collection, analysis and use
    often rely on bespoke software.
                     Parallel systems
   Donor agenda regarding data collection, unsustainable

   Data collection, analysis and use for policy is fragmented
     – Uganda/Nepal: lack of unified data linked to SWAPs
     – Private sector is often not covered (India/Uganda)
   Multiple reporting requirements (Rwanda/India).

   Lack of inter-sectoral information systems and unified quality
    standards. (Uganda/ Rwanda)

   Vertical donors-supported programmes often function well in
    the short-term but may distort wider systems (e.g. Georgia &
        Information flows & level of use

   One-way traffic for information
     – Disaggregated data not available at sub-national level
     – Information intended to be used locally, is used at national level, or for
       different purpose reflecting governance & aid coordination

   Information that is not aggregated nationally, less useful

   Governance and stewardship at local level needs to be able to draw
    effectively on aggregate & disaggregate data
     – Disaggregated data feeds effectively into local planning when linked to
       decentralised decision-making (TEHIP)

   Peer comparisons at district level – productive vs unhelpful
Factors facilitating measurement & use of data
   Health system monitoring embedded within reform process
     – SWAPs/ PRSP in Uganda, Rwanda; district autonomy (TEHIP)
   Unintended consequences (Afghanistan)
     – Selective use of data internationally (user fees/HIV, in Uganda)

   In post-conflict settings, the aid influx promotes monitoring health
    systems & early warning systems. Possible inefficiencies.
   The importance of governance
     – Channels for policy exist (annual reviews, SWAPs meetings) & comparable
     – Communities and non-health system stakeholders involved
   Large-scale data collection exercises are resource-intensive and not
    synchronised with the policy process (some In-DEPTH/ LSMS).
   Technology, appropriate to context
Effective health systems monitoring requires:
   Capacity: to collect or use existing data, analyse, inform policy
   Ownership
   Coherence between domestic and external demands
   Coherence between external agencies
   Coherence between system-wide monitoring and vertical
    programmes performance measurement
   Coherence between assessing the performance of different system
   Domestic governance
   Impact measurement to ensure sustainability/reform (scaling up)
   Foster partnership between stakeholders

Georgia       George Gotsadze
India         Barun Kanjilal
Rwanda        Vianney Nizeyimana
Tanzania      Graham Reid
Uganda        Valeria Oliveira-Cruz
              Freddy Ssengoba

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